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Does climate policy uncertainty affect Chinese stock market volatility?

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  • Chen, Zhonglu
  • Zhang, Li
  • Weng, Chen

Abstract

Global warming forces policymakers to change climate policies to achieve global carbon neutrality targets. Although policy changes and developments affect financial asset price volatility, unpredictable climate policy changes make policy decisions less certain. This study investigates the spillover effects of climate policy uncertainty (CPU) on Chinese stock market volatility in the realized GARCH-MIDAS framework. To capture more information on asset price volatility, we further employ 5-min high-frequency data. The empirical results provide strong evidence to support that our strategy can successfully improve volatility forecasting accuracy. First, in-sample results indicate that CPU has a significant effect on stock price volatility. Second, out-of-sample tests confirm that the extended model that considers both CPU and high-frequency data exhibits the best predictive ability. In addition, various robustness tests strongly demonstrate our main findings. Thus, this paper demonstrates that weather effects exist in the stock market and reminds investors that they should pay more attention to climate policies in the current period of the climate crisis.

Suggested Citation

  • Chen, Zhonglu & Zhang, Li & Weng, Chen, 2023. "Does climate policy uncertainty affect Chinese stock market volatility?," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 369-381.
  • Handle: RePEc:eee:reveco:v:84:y:2023:i:c:p:369-381
    DOI: 10.1016/j.iref.2022.11.030
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    Cited by:

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    2. Yuqin Zhou & Shan Wu & Zhenhua Liu & Lavinia Rognone, 2023. "The asymmetric effects of climate risk on higher-moment connectedness among carbon, energy and metals markets," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    3. Huthaifa Sameeh Alqaralleh, 2023. "The extreme spillover from climate policy uncertainty to the Chinese sector stock market: wavelet time-varying approach," Letters in Spatial and Resource Sciences, Springer, vol. 16(1), pages 1-17, December.

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    More about this item

    Keywords

    Climate policy uncertainty; Chinese stock market; Volatility forecast; Realized GARCH-MIDAS;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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